layoutlmv3-final-v5-BIE
This model is a fine-tuned version of microsoft/layoutlmv3-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.9239
- Precision: 0.9019
- Recall: 0.9013
- F1: 0.9016
- Accuracy: 0.7757
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 500
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
No log | 2.56 | 100 | 2.2304 | 0.6394 | 0.5974 | 0.6177 | 0.5199 |
No log | 5.13 | 200 | 1.3910 | 0.8278 | 0.8224 | 0.8251 | 0.6924 |
No log | 7.69 | 300 | 1.0866 | 0.8749 | 0.8743 | 0.8746 | 0.7385 |
No log | 10.26 | 400 | 0.9587 | 0.8947 | 0.8941 | 0.8944 | 0.7663 |
1.6438 | 12.82 | 500 | 0.9239 | 0.9019 | 0.9013 | 0.9016 | 0.7757 |
Framework versions
- Transformers 4.30.0.dev0
- Pytorch 1.8.0+cu101
- Datasets 2.12.0
- Tokenizers 0.13.3
- Downloads last month
- 4
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.